Indicators of an individual's physiological health (“health-indicators”)—for example and not by way of limitation: heart rate, heart rate variability, blood pressure, and ECG (electrocardiogram) to name a few—can be measured or calculated at any discrete point or points in time from data collected to measure the health-indicators. In many cases, the value of the health-indicator at a particular time, or a change over time provides information regarding the state of an individual's health. A low or high heart rate or blood pressure, or an ECG that clearly demonstrate myocardial ischemia, for example, may demonstrate the need for immediate intervention. But, readings, a series of readings, or changes to the readings over time of these indicators may provide information not recognized by the user or even a health professional as needing attention.
Arrhythmias, for example, may occur continuously or may occur intermittently. Continuously occurring arrhythmias may be diagnosed most definitively from an electrocardiogram of an individual. Because a continuous arrhythmia is always present, ECG analysis may be applied at any time in order to diagnose the arrhythmia. An ECG may also be used to diagnose intermittent arrhythmias. However, because intermittent arrhythmias may be asymptomatic and/or are by definition intermittent, diagnosis presents challenges of applying the diagnostic technique at the time when the individual is experiencing the arrhythmia. Thus, actual diagnosis of intermittent arrhythmias is notoriously difficult. This particular difficulty is compounded with asymptomatic arrhythmias, which account for nearly 40% of arrhythmias in the US. Boriani G. and Pettorelli D., Atrial Fibrillation Burden and Atrial Fibrillation type: Clinical Significance and Impact on the Risk of Stroke and Decision Making for Long-term Anticoagulation, Vascul Pharmacol., 83:26-35 (August 2016), pp. 26.
Sensors and mobile electronics technologies exist which permit frequent or continuous monitoring and recording of health-indicators. However, the capability of these sensor platforms often exceeds that of conventional medical science to interpret the data they produce. The physiological significance of health-indicator parameters, like heart rate, are frequently well defined only in specific medical contexts: for instance, heart rate is conventionally evaluated as a single scalar value out of context from other data/information that may impact the health-indicator. A resting heart rate in the range of 60-100 beats per minute (BPM) may be considered normal. A user may generally measure their resting heart rate manually once or twice per day.
A mobile sensor platform (for example: a mobile blood pressure cuff; mobile heart rate monitor; or mobile ECG device) may be capable of monitoring the health-indicator (e.g., heart rate) continuously, e.g., producing a measurement every second or every 5 seconds, while simultaneously also acquiring other data about the user such as and without limitation: activity level, body position, and environmental parameters like air temperature, barometric pressure, location, etc. In a 24-hour period, this may result in many thousands of independent health-indicator measurements. In contrast to a measurement once or twice a day, there is relatively little data or medical consensus on what a “normal” sequence of thousands of measurements looks like.
Devices presently used to continuously measure health-indicators of users/patients range from bulky, invasive, and inconvenient to simple wearable or handheld mobile devices. Presently, these devices do not provide the capability to effectively utilize the data to continuously monitor a person's heath. It is up to a user or health professional to assess the health-indicators in light of other factors that may impact these health-indicators to determine the health status of the user.